- Collect Knowledge about ECG interpretation
- Get a dataset of ECG with classification
- Train a computer vision model to be able to classify the ECG
- Deploy the model in a real environment with specialist supervision to test the accuracy.
- A good model must never hide an alarming case and consider it as normal or less risky so this is the major performance score that will be monitored.
The participants will be able to apply AI for one of the most recurrent scenarios in healthcare: the classification of medical imaging. E-health is starting to deploy AI and this project will bring valuable learning opportunities.